Abstract: The transmission threshold （ \beta _C ） and the basic reproduction number （ R_0 ） serve as core parameters for quantifying transmission risk and guiding epidemic control strategies. The former defines the critical point for sustained transmission of infectious diseases, while the latter measures the average number of secondary infections caused by a single infected individual. Their theoretical analysis is of crucial importance to research in infectious disease dynamics. Currently, the correspondence between theoretical analysis methods and model construction remains unclear, constraining the efficiency and accuracy of transmission parameter interpretation. Based on a complex network transmission dynamics framework, this study integrates classical epidemic models with multiscale theoretical analysis methods to systematically establish a theoretical analysis system for transmission parameters—spanning methodological principles, mathematical representation, and case studies—and further constructs a "model-theoretical analysis method" matching decision mechanism. The research results not only enhance the theoretical foundation of complex network transmission dynamics and provide researchers and public health departments with a clear theoretical analysis pathway and model selection basis, effectively reducing the threshold for selecting theoretical analysis methods, but also offer practical methodological support for the construction and validation of infectious disease prediction models.